Dynamic OLS Estimator Research Articles

Analyzing the role of green innovation and public-private partnerships in achieving sustainable development goals: a novel policy framework.

The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13.

Financial development and real exchange rate misalignments effects on environmental pollution

The research examined the influence of the fundamental exchange rate misalignment and Least Developed Countries (LDCs) in Asia and Africa’s financial development on CO2 emissions in Asian countries using panel data from 1970 to 2021. The methodology consists of ARDL bound testing and PMG/ARDL estimators with dynamic OLS estimators. The results reveal that the long-run real exchange rates for least developed countries (LDCs) are expected to rise in CO2 emissions in Asian and African countries with improved trade and net foreign asset positions. The relative productivity and trade openness also increase the exchange rate, which also plays a vital role in the growth of CO2 emissions. Except for Egypt, all least developed countries (LDCs) currencies are overpriced throughout the research period at the same time; it would be harmed by increased openness, foreign direct investment inflows, and currency misalignment. Overvaluation harms Bahrain’s economic growth. In comparison, undervaluation helps Egypt that currency misalignment does not affect financial growth in any LDCs over the long run. In the short-run, more real investment, net foreign assets, and official assistance inflows would enhance financial growth in Qatar, Bahrain, Singapore, and South Korea. In contrast, trade openness would slow it down in Egypt and Kuwait. The study suggested that the poor economic performance is due to RER misalignment, which occurs when exchange rate policies are improper and causes a rise in CO2 emissions in many developing countries.

Factors That Determine International Competitiveness of Agricultural Products in Latin America 1990-2020

Agriculture has played a crucial role in the economy and the development of many countries. Moreover, the basic needs for human survival are; food, shelter and cloth are link on agricultural production. Most developed countries see that agriculture provides them with food and raw materials for different goods such as (shelter, medicine, fuel and clothing) which has led to increase in incomes, livelihoods and standard of living. This study aimed at analysing the relationship between International competitiveness of agricultural products, with area, fertilizer, labour force, economic growth, foreign direct investment, exchange rate and inflation rate in Latin America during the period of 1991-2019. In this study, panel data econometric method was used, as well as cross-section dependence (Pesaran test), unit root (cross-section Augumented Dickey Fuller and Cross-sectional Im, Pesaran, and Shin tests), cointergration (Pedroni and Fisher-Johansen tests), and heterogeneous causality (Pedroni and Fisher-Johansen tests) (Hurlin and Dumitrescu test). The results reveal that the model has cross-sectional dependency and that they are integrated at one I (1). The "fully modified OLS and dynamic OLS estimators" were used to examine the existence of a long-term relationship and it was found that a long-term relationship existed between the selected variables. The study revealed a positive significant relationship between International Competitiveness of the agricultural raw material and area, fertilizer, labour force, economic growth, foreign direct investment, while international competitiveness has negative relationship with exchange rate, and inflation. The economy policy recommendations deducted from this investigation is that Foreign Direct Investment and labour force have a positive contribution to the increase of International Competitiveness of agricultural products.

Do Economic Policy Uncertainty and Geopolitical Risk Lead to Environmental Degradation? Evidence from Emerging Economies

Since the turn of twenty first century, economic policy uncertainty (EPU) and geopolitical risk (GPR) have escalated across the globe. These two factors have both economic and environmental impacts. However, there exists dearth of literature that expounds the impact of EPU and GPR on environmental degradation. This study, therefore, probes the impact of EPU and GPR on ecological footprint (proxy for environmental degradation) in selected emerging economies. Cross-sectional dependence test, slope heterogeneity test, Westerlund co-integration test, fully modified least ordinary least square estimator, dynamic OLS estimator, and augmented mean group estimator are employed to conduct the robust analyses. The findings reveal that EPU and non-renewable energy consumption escalate ecological footprint, whereas GPR and renewable energy plunge ecological footprint. In addition, findings from the causality test reveal both uni-directional and bi-directional causality between a few variables. Based on the findings, we deduce several policy implications to accomplish the sustainable development goals in emerging economies.

Remittances and corruption in Nigeria

PurposeIn this paper, we investigate the impact of remittances on control of corruption in Nigeria for a period of 1986–2016.Design/methodology/approachThe study uses ARDL modeling framework, dynamic OLS estimation, variance decomposition and impulse response analysis to examine the relationship between the two variables.FindingsThe study finds that remittances significantly improve the control of corruption in Nigeria. We further examine the robustness test of the results using dynamic OLS estimation, variance decomposition and impulse response analysis. Our results remain significant and consistent to the earlier one reported in ARDL framework which supports the extant literature.Practical implicationsOur study suggests that international remittances can be used, through the cross-border transfer of norms and practices, to significantly impact the socioeconomic progresses of a country by reducing corruption.Originality/valueThe existing studies on the relationship between corruption and remittances document conflicting results. In addition, study on corruption - remittances nexus that specifically focuses on any African country is largely absent despite the fact that most of the countries in the region are recognized as highly corrupt. This paper provides insights on how remittances can be used as part of tool kits to control corruption in African nation.

Energy Consumption and Financial Development in NAFTA Countries, 1971–2015

To satisfy human needs and desires, it is necessary to produce goods and services that require the use of some production factors, such as labor, capital, and energy, among others. Nowadays, energy is a key production factor for economic activity in all countries. The main objective of this paper is to analyze the relationship between energy, economic growth, urbanization, and financial development in the country-members of the North American Free Trade Agreement (NAFTA) during the period of 1971–2015. Panel data Econometric methods are applied in this research, namely cross-section dependence (Pesaran test), unit root (Cross-sectional Augmented Dickey Fuller and Cross-sectional Im, Pesaran, and Shin tests), cointegration (Kao and Fisher–Johansen tests), and heterogeneous causality (Hurlin and Dumitrescu test). The results achieved in this research demonstrate that the variables of this model are characterized by a cross-section dependence, and they are integrated in order one. An equilibrium or long-term relationship between them exists. By means of the Fully Modified OLS and Dynamic OLS estimators it this demonstrated that there is a positive relationship between GDP and EC, while there is a negative relationship between FD, CPI, URB, and TO and EC. The economic policy recommendations drawn from this investigation are that financial development promotion, urbanization, and trade openness may contribute to reducing energy consumption in these countries.

The export performance of the euro area: A panel quantile regression approach

This paper examines the impact of relevant factors on merchandise exports, volume growth, and the competitiveness of euro-area countries. It uses panel regressions to explain the development of merchandise exports in the euro-area countries by various price/cost competitiveness indicators, development of foreign and domestic demand, and the structure of merchandise exports. A cointegration analysis of panel time series was established by applying econometric tests and the cointegration equation for the period 1999-2018 was estimated using FMOLS (Fully Modified OLS) and DOLS (Dynamic OLS) estimators. We show that the increase in the share of information communication technology (ICT) product exports in the total merchandise exports of euro-area members had a positive impact on their export performance. The empirical results show that foreign demand has a positive impact on real merchandise exports, while the estimated coefficients decreased from the lower to upper quantiles. The results regarding price and cost competitiveness differ depending on the choice of indicators, but in general they are less robust. Therefore, we conclude that in the long run, non-price factors will play an increasingly important role in strengthening the competitive position of euro-area countries in international markets.

Monetary union in Latin America: an assessment in the context of optimum currency area

ABSTRACT The article applies the optimum currency area (OCA) theory to Latin America to assess the potential of a monetary union in Latin America and in its major existing regional trade agreements (RTAs). According to OCA criteria we find that Latin America is far from being an optimum currency area, as its countries’ exposure to asymmetric shocks is high and their capacities to adjust in response to macroeconomic disturbances are limited. Using a panel of 20 Latin American countries from 1990 to 2014, we apply the dynamic OLS estimation techniques to estimate the costs and benefits of a potential monetary union in Latin America and in its various RTAs. to estimate the costs and benefits of a potential monetary union in Latin America and in its various RTAs. We find that the costs are high, because Latin America’s economies are vulnerable to severe macroeconomic disturbances and its RTAs differ significantly in their response to negative demand shocks. Most of the monetary efficiency gains are shown to be the result of a common restrictive monetary policy which would result in higher FDI inflows and, to a more limited extent, increased GDP, both overall and per capita. Although Central American countries are shown to be most suitable for further monetary integration, we conclude that Latin American countries should head first towards greater economic and political integration.

Health and Economic Growth Nexus: Evidence from Selected Sub-Saharan African (SSA) Countries

This article examines the effect of health on long-run economic growth in 35 selected sub-Saharan African (SSA) countries using panel data covering the period 1997–2016. Data were analysed using panel co-integration tests, panel Granger causality tests and the dynamic OLS estimator. The results show that health human capital is a significant determinant of long-run economic growth in SSA. In particular, a percentage increase in health human capital proxied by per capita health expenditure increases growth by 0.207 per cent. The prime contribution of this article to the literature lies in the results of the novel interaction between health human capital and institutional quality. More precisely, by using the dynamic panel least square estimation technique, we found that the effect of institutional quality on economic growth is positive and robust only when it is interacted with the required health human capital. It is further revealed that the causal link between economic growth and health is bidirectional.

Technology spillover effects within Spanish communities

ABSTRACTThe article uses panel data for the period 1990–2010 to estimate technology spillover effects on 17 Spanish communities. Accounting for nonstationarity and cointegration, we use the dynamic OLS estimator to estimate the impact of domestic and non-domestic R&D capital stock on labour productivity of Spanish communities, taking into account trade-, migration- and foreign direct investment (FDI)-related technology diffusion channels. We find significant trade-related spillover effects within Spanish communities and from EU countries. On average, an increase in the non-domestic R&D stock of 1% increases their labour productivity between 0.02% and 0.12% if related to bilateral trade pattern. Moreover, migration within Spanish communities has a negative impact ranging between −0.07% and −0.16% on labour productivity as the impact of inward migration is dominated by outward migration. There is no robust impact from FDI inflows of OECD countries in general or EU countries in particular. Finally, the domestic R&D stock, physical capital and human capital are shown to be significant drivers for labour productivity in Spain no matter if non-domestic (local or foreign) spillover effects are trade-, migration- or FDI-related.

Foreign investors’ influence on the real estate market capitalization rate – evidence from a small open economy

ABSTRACTThis article adds to the scarce literature on the influence of international investment flows on local real estate values. We hypothesize that a greater foreign-investor presence in a real estate market results in a lower capitalization rate and examine whether this holds true in the Helsinki CBD office market in Finland. This market provides an interesting case study by being part of a small open economy, in which the presence of foreign investors has substantially varied over time. The Dynamic OLS estimations using data for the period 1990–2015 provide support for the hypothesis. The baseline results show a highly statistically significant negative impact of foreign-investor participation on the capitalization rate, the point estimates indicating that a 10% point growth in the share of foreign buyers of the total transaction volume decreases the cap rate by approximately 30 basis points.

Empirical Analysis of Linkages between Shanghai and Bombay Stock Markets

This paper explores the possible linkages between Shanghai and Bombay stock markets, accounting for complimentarity (through direct linkages) and substitutability (through indirect linkages) features between China and India to confirm real linkages in physical world. We employ a Dynamic OLS estimation proposed by Stock and Watson (1994) to estimate long run relationship between two variables. Considering the long memory feature of financial data, we apply the ARFIMA regression to our cointegrated residual derived from Dynamic OLS estimation. While differencing cointegrated residual with fractionally integrated order of d value, we estimate the long term and short dynamic relations of index returns in two stock markets, with the help of VECM equation. Furthermore, we apply a DCC-MGARCH model to analyze ARCH effect, GARCH effect, and volatility transmission between two stock markets. We use Quantile regression approach to study dependence structure and intensity at different quantiles between two markets. Dummy variables are taken to distinguish pre-crisis periods and in crisis, post-crisis periods.

On the Relationship between Estimate and Its <i>t</i> Value

It is generally believed that the signs of the estimated coefficient and its t value should be the same. This paper, however, shows that there may be an inconsistency in the signs of the estimated coefficient and its t value when we use the group mean dynamic OLS estimator developed by Pedroni (2001).

Technology spillover effects and economic integration: evidence from integrating EU countries

The article uses time series for the period 1981–2008 to estimate the impact of foreign technology spillover effects on Greece, Ireland, Portugal and Spain, representing the integrating European Union (EU) countries. I restrict technology diffusion to EU-12 countries and compare the results to unrestricted technology diffusion from a sample of 32 OECD countries. Accounting for nonstationarity and co-integration, the dynamic OLS estimator is used to estimate the impact of foreign R&D stock on labour productivity, taking into account patent-, trade- and FDI-related technology diffusion channels. I find empirical evidence for trade-related foreign technology spillover effects for Greece and Ireland if technology diffusion is unrestricted. Restricting technology diffusion to EU-12 countries, there are significant foreign technology spillover effects from European integration for Portugal (patent related) and Spain (trade and FDI related). Moreover, the domestic R&D stock and education are significant drivers for labour productivity in integrating EU countries. The empirical results are robust for different regression specifications and sources of technology diffusion.

Asymptotic properties of the efficient estimators for cointegrating regression models with serially dependent errors

Abstract In this paper, we analytically investigate three efficient estimators for cointegrating regression models: Phillips and Hansen’s [Phillips, P.C.B., Hansen, B.E., 1990. Statistical inference in instrumental variables regression with I(1) processes. Review of Economic Studies 57, 99–125] fully modified OLS estimator, Park’s [Park, J.Y., 1992. Canonical cointegrating regressions. Econometrica 60, 119–143] canonical cointegrating regression estimator, and Saikkonen’s [Saikkonen, P., 1991. Asymptotically efficient estimation of cointegration regressions. Econometric Theory 7, 1–21] dynamic OLS estimator. We consider the case where the regression errors are moderately serially correlated and the AR coefficient in the regression errors approaches 1 at a rate slower than 1 / T , where T represents the sample size. We derive the limiting distributions of the efficient estimators under this system and find that they depend on the approaching rate of the AR coefficient. If the rate is slow enough, efficiency is established for the three estimators; however, if the approaching rate is relatively faster, the estimators will have the same limiting distribution as the OLS estimator. For the intermediate case, the second-order bias of the OLS estimator is partially eliminated by the efficient methods. This result explains why, in finite samples, the effect of the efficient methods diminishes as the serial correlation in the regression errors becomes stronger. We also propose to modify the existing efficient estimators in order to eliminate the second-order bias, which possibly remains in the efficient estimators. Using Monte Carlo simulations, we demonstrate that our modification is effective when the regression errors are moderately serially correlated and the simultaneous correlation is relatively strong.

An empirical test of the environmental Kuznets curve in China: A panel cointegration approach

Abstract This paper investigates the relationship between environmental pollution and economic growth in China based on the environmental Kuznets curve hypothesis, using Chinese provincial data over 1985–2005. Waste gas, waste water and solid wastes are used as environmental indicators and GDP is used as the economic indicator. It is found by panel cointegration test that there is a long-run cointegrating relationship between the per capita emission of three pollutants and the per capita GDP. According to comparisons with the dynamic OLS estimator and the Within OLS estimator, we find that panel cointegration estimation is preferable for all pollutants except for solid wastes. The results also show that all three pollutants are inverse U-shaped, and water pollution has been improved earlier than gas pollution and solid pollution.

PPP tests in cointegrated panels: evidence from Asian developing countries

This study tests the relative version of purchasing power parity (PPP) for a set of ten Asian developing countries using a panel cointegration framework. A ‘between-dimension’ dynamic OLS estimator as proposed by Pedroni is employed. The test results overwhelmingly reject the PPP hypothesis.

On the Estimation and Inference of a Cointegrated Regression in Panel Data

The main contribution of this paper is to add to the literature by suggesting a dynamic OLS (DOLS) estimator and providing a serious comparison of the finite sample properties of the OLS, fully modified OLS (FMOLS), and DOLS estimators in panel cointegrated regression models. Monte Carlo results illustrate the sampling behavior of the proposed estimators and show that (1) the OLS estimator has a non-negligible bias in finite samples, (2) the FMOLS estimator does not improve over the OLS estimator in general, and (3) the DOLS outperforms both the OLS and FMOLS estimators.